Extraction of semantic relation

ABSTRACT

A computer-implemented method for extracting semantic relations is disclosed. In the method, a plurality of hierarchal structures that originates from a corpus of documents is obtained. Each hierarchal structure includes a plurality of elements having respective recitations included in a corresponding document. In the method, for each predetermined relationship between ancestor and descendant elements in the hierarchal structures, a first keyword list is extracted from the ancestor element and a second keyword list is extracted from the descendant element. A statistical index is calculated for each pair of first and second keywords using the first keyword lists and the second keyword lists. The index indicates a strength of association between the first and second keywords. In the method, a candidate list of keyword pairs having semantic relationships is output using the statistical index calculated for each pair.

BACKGROUND Technical Field

The present disclosure, generally, relates to semantic relationextraction, more particularly, to techniques for extracting semanticrelation from a corpus of documents.

Description of the Related Art

Semantic relation such as hypernym/hyponym relation is key informationfor various analysis tasks, including prior art search and patent mapcreation, etc. There are many thesauri covering the hypernym/hyponymrelation and other semantic relation. However, the existing thesauri arenot always applicable to patent analysis since highly technical contentsare generally described in patent documents with patent-specific wordsand phrases that may not be covered in the existing thesauri.Especially, the hypernym/hyponym relation may change depending ontechnical fields. Furthermore, although such semantic relation is oftendefined in documents, the relation is not always rigidly described in aform such as “is-a” expression in the documents.

Therefore, there is a need for developing novel technology capable ofextracting semantic relation from a given corpus of documents whilereducing manual work.

SUMMARY

According to an embodiment of the present invention, acomputer-implemented method for extracting semantic relation isprovided. The method includes obtaining a plurality of hierarchalstructures originating from a corpus of documents. Each hierarchalstructure includes a plurality of elements having respective recitationsthat are included in a corresponding document. The method also includesextracting, for each predetermined relation between ancestor anddescendant elements in the hierarchal structures, a first keyword listfrom the ancestor element and a second keyword list from the descendantelement. The method further includes calculating, for each pair of firstand second keywords, a statistical index indicating strength ofassociation between the first and second keywords, using a first keywordlists and the second keyword lists. The method includes furtheroutputting a candidate list of keyword pairs having semantic relationusing the statistical index calculated for each pair.

Computer systems and computer program products relating to one or moreaspects of the present invention are also described and claimed herein.

Additional features and advantages are realized through the techniquesof the present invention. Other embodiments and aspects of the inventionare described in detail herein and are considered a part of the claimedinvention.

BRIEF DESCRIPTION OF THE DRAWINGS

The subject matter, which is regarded as the invention, is particularlypointed out and distinctly claimed in the claims at the conclusion ofthe specification. The foregoing and other features and advantages ofthe invention are apparent from the following detailed description takenin conjunction with the accompanying drawings in which:

FIG. 1 illustrates a block diagram of a hypernym-hyponym extractionsystem for extracting hypernym-hyponym relation from a corpus of patentdocuments according to an exemplary embodiment of the present invention;

FIG. 2 is a first half of a flowchart depicting a process for extractinghypernym-hyponym relation from a corpus of patent documents according toan exemplary embodiment of the present invention;

FIG. 3 is a latter half of the flowchart depicting the process forextracting the hypernym-hyponym relation from the corpus of the patentdocuments according to the exemplary embodiment of the presentinvention;

FIG. 4 depicts an example of a series of patent claims as an input for ahypernym-hyponym extraction according to the exemplary embodiment of thepresent invention;

FIG. 5 depicts a schematic of way of building a claim structure as anintermediate data structure in the hypernym-hyponym extraction accordingto the exemplary embodiment of the present invention;

FIG. 6 depicts schematics of ways of extracting parent and childkeywords from recitations of claim elements during the hypernym-hyponymextraction according to the exemplary embodiment of the presentinvention;

FIG. 7 illustrates a schematic of a graphical user interface displayinga result of hypernym-hyponym relation extraction according to anexemplary embodiment of the present invention;

FIG. 8 shows an example of a candidate list obtained experimentally byperforming the extraction process using a patent claim section of patentspecifications having IPC=H01M according to an exemplary embodiment ofthe present invention;

FIG. 9 shows other example of a candidate list obtained experimentallyby performing the extraction process using the patent claim section ofthe patent specifications having IPC=H01M according to an exemplaryembodiment of the present invention;

FIG. 10 shows another example of a candidate list obtainedexperimentally by performing the extraction process using the patentclaim section of the patent specifications having IPC=H01M according toan exemplary embodiment of the present invention; and

FIG. 11 depicts a computer system according to one or more embodiment ofthe present invention.

DETAILED DESCRIPTION

Hereinafter, the present invention will be described with respect toparticular embodiments, but it will be understood by those skilled inthe art that the embodiments described below are mentioned only by wayof examples and are not intended to limit the scope of the presentinvention.

One or more embodiments according to the present invention are directedto computer-implemented methods, computer systems and computer programproducts for extracting semantic relation from a corpus of documents. Inparticular embodiments the semantic relation to be extracted may behypernym-hyponym relation and the corpus of the documents under analysismay be a corpus of patent documents, including a patent claim section ina patent specification.

Hereinafter, referring to a series of FIGS. 1-7 , a computer system anda method for extracting hypernym-hyponym relation from a given corpus ofpatent documents according to an exemplary embodiment of the presentinvention will be described. Then, referring to a series of FIGS. 8-10 ,experimental studies on the novel hypernym-hyponym relation extractionaccording to the exemplary embodiment of the present invention will bedescribed. Finally, referring to FIG. 11 , a hardware configuration of acomputer system according to one or more embodiments of the presentinvention will be described.

Exemplary Embodiment

Now, referring to a series of FIGS. 1-7 , a hypernym-hyponym extractionsystem and a method for extracting hypernym-hyponym relation from acorpus of patent documents are described.

FIG. 1 illustrates a block diagram of a hypernym-hyponym extractionsystem (hereinafter, simply referred to as “extraction system”) 100. InFIG. 1 , there are the extraction system 100; a patent document corpus102 from which the extraction system 100 reads patent documents; and ahypernym-hyponym dictionary store 106 to which a keyword pair havinghypernym-hyponym relation extracted by the extraction system 100 isstored.

As shown in FIG. 1 , the extraction system 100 includes a claimstructure building module 110 that builds data structures representingclaims from patent documents in the patent document corpus 102; akeyword extraction module 120 that extracts keywords based on the datastructures; an index calculation module 130 that calculates astatistical index for each keyword pair; a filtering module 140 thatperforms filtering of the keyword pairs using the statistical index; andan output module 150 that outputs a filtered keyword pair as a candidateof a hypernym-hyponym relation.

The patent document corpus 102 is configured to store a collection ofpatent documents, each of which includes at least a patent claim sectionof a patent specification of a given patent or patent application. Thepatent document corpus 102 is stored on a storage device, such as RAM(Random Access Memory), HDD (Hard Disk Drive), SSD (Solid State Drive),etc. The document corpus 102 may include scanned versions of hard-copy(e.g., paper copies) documents as well as documents originating indigital formats. In the case of paper copies of the documents, scanningdevices, such as peripheral 24 (FIG. 11 ) can be employed to scan thedocument to transform the document into electronic formats. Scanningtechnologies, such as optical character recognition (OCR), may beapplied to the document either during or after scanning of the documentby the scanning device to create, for example, a portable documentformat (PDF) version or other format versions of the document withmachine-encoded text.

The patent claim section includes recitations of one or more patentclaims. In a case that plural claims are included in the patent claimsection, there may be two types of patent claims; an independent claim,which is standalone type and is directed to essential features of aninvention, and a dependent claim, which depends on a single claim or onseveral claims and adds further limitation on the patent claim(s)followed by the dependent claim. The patent claim defines the scope ofthe protection given by the granted patent or sought in the patentapplication.

The claim structure building module 110 is configured to parse eachpatent document to obtain a plurality of hierarchal structures thatoriginates from the patent documents in the patent document corpus 102.Each hierarchal structure includes a plurality of claim elements havingrespective recitations that are included in a corresponding patentdocument and represents dependency within the claim elements. Eachhierarchal structure represents dependency between the claim elements ina single patent claim or dependency between the claim elements in aseries of an independent claim and one or more dependent claims. Whenthe patent document includes two or more independent claims, two or morehierarchal structures would be obtained. Note that the claim elementcorresponds to a part that can be decomposed from a single patent claim,or an entire patent claim. Hereinafter, the hierarchal structure isreferred to as a claim structure.

FIG. 1 shows a more detailed diagram of the claim structure buildingmodule 110. The claim structure building module 110 may include a claimdecomposition module 112 that decomposes each patent document into oneor more claim elements; and a dependency extraction module 114 thatextracts dependency within the claim elements.

The claim decomposition module 112 is configured to decompose one ormore patent claims recited in each patent document into a plurality ofclaim elements. As described above, each claim element in the claimstructure represents a part of a patent claim or an entire patent claim.The independent claim is preferable to be decomposed into a plurality ofclaim elements since the independent claim generally includes aplurality of limitations necessary to define an invention. The dependentclaim itself can be treated as a claim element since the dependent claimoften includes a limitation relating to only a single antecedent in theclaim followed by the dependent claim. Alternatively, the dependentclaim can be decomposed into a plurality of claim elements since thedependent claim often includes limitations relating to two or moreantecedents recited in the claim followed by the dependent claim. Thedecomposition can be done by using any known technique, including usingcue phrases, using line breaks or other structure extraction method.

The dependency extraction module 114 is configured to extractdependencies between the decomposed claim elements to build a claimstructure. By performing the dependency extraction, the claim structurethat has the decomposed claim elements and the extracted dependencies asnodes and edges, respectively, are built. Thus, a parent-childrelationship may be defined between claim elements. The dependencies tobe extracted includes a dependency between claim elements in one patentclaim as well as a dependency between a claim element in one patentclaim and a claim element in another patent claim or another patentclaim itself. The depth for each element is calculated by a knownalgorithm and the parent-child relationship is identified by using anoverlapping term that connects element-element dependency orelement-dependent claim dependency.

As shown in FIG. 1 , there is a claim structure store 104. The claimstructure building module 110 is configured to store the built claimstructure into the claim structure store 104. The claim structure store104 is provided by the storage device, such as RAM, HDD, SSD, etc. Inthe described embodiment, the claim structures stored in the claimstructure store 104 are described as being extracted by the claimstructure building module 110 in the extraction system 100. However, theclaim structures stored in the claim structure store 104 may not belimited and may include a claim structure extracted by another moduleoutside of the extraction system 100.

The keyword extraction module 120 is configured to extract, for eachparent-child relationship between one parent element and one childelement in the claim structures, a parent keyword list from the parentelement and a child keyword list from the child element. The keywordextraction can be done by using any known keyword extraction technique,including TF-IDF (Term Frequency-Inverse Document Frequency), BM25,TexRank approaches, etc.

Note that, in the described embodiment, the parent-child relationship isemployed to prepare pairs of the parent and child keyword lists.However, in other embodiment, certain ancestor-descendant relationshipssuch as grandparent-grandchild relation may also be contemplated. Alsonote that the keyword in the keyword list may be a single word orconcatenated multiple words and may include a so-called key phrase. Astop word removal may be performed to exclude common words such as “is”,“of”, “a”, etc. from the keywords. Also, lemmatization and/or stemmingmay also be performed before the keyword extraction.

More specifically, the keyword extraction module 120 may read the claimstructures stored in the claim structure store 104 and extract, for eachparent-child relationship in the claim structures, one or more parentkeywords from the recitation of the parent element and one or more childkeywords from the recitation of the child element to have the parentkeyword list and the child keyword list. One keyword in the parentkeyword list and one keyword in the child keyword list may be combinedto enumerate an instance of a pair of parent and child keywords. Theways of extracting the parent and child keyword lists from the parentand child elements will be described in more detail later.

The index calculation module 130 is configured to calculate, for eachpair of the parent and child keywords, a statistical index thatindicates strength of association between the parent and child keywords,using pairs of the parent and child keyword lists that are obtained fromthe collection of the patent documents in the patent document corpus102.

Also note that the patent documents to be analyzed can be limited bydesignation of an attribute, which may include an IPC (InternationalPatent Classification) symbol. For example, a collection of patentshaving a specific IPC symbol prefix is designated to be analyzed. Thus,the pairs of the parent and child keyword lists used by the indexcalculation module 130 may be obtained from the collection of thepatents having the specific IPC symbol prefix in the patent documentcorpus 102.

In a particular embodiment, the statistical index is, but not limitedto, a pointwise mutual information (PMI) that measures an association ofan event where the parent keyword appears in recitation of the parentelements (or the parent keyword lists) and an event where the childkeyword appears in the child elements (or the child keyword lists).

The filtering module 140 is configured to filter the pairs of the parentand child keywords extracted by the keyword extraction module 120 usingthe statistical index that is calculated by the index calculation module130. The output of the filtering module 140 is used to create acandidate list of keyword pairs having a hypernym-hyponym relationship.If a pair has a statistical index higher than a predetermined threshold,the pair remains in the resultant candidate list. Otherwise, the pair isdiscarded from the resultant candidate list.

In embodiments, additional filtering and/or evaluation can be performedto improve reliability and robustness of the resultant candidate list.

In an embodiment, the filtering module 140 may be further configured todetermine whether or not each keyword pair also has a reverserelationship. The existence of the reverse relationship can beidentified by confirming whether or not a statistical index calculatedfor a reverse pair (the parent and the child of the original pair aretreated as a child and a parent of a reverse pair) is higher than apredetermined threshold. The keyword pair having the reverserelationship may be removed from the resultant candidate list of thekeyword pairs (as an additional filtering) or flagged to notify that thepaired keywords may have a bidirectional relationship (as an additionalevaluation).

In further embodiments, the filtering module 140 may be furtherconfigured to add several flags to each keyword pair in the candidatelist to indicate the reliability of each keyword pair in the candidatelist (as additional evaluations). More detail about the flags will bedescribed later.

The output module 150 is configured to output the candidate list of thekeyword pairs having the hypernym-hyponym relationship based on theresult of the filtering module 140 that uses the statistical indexcalculated for each pair to perform the filtering and/or evaluation.

The remaining keyword pairs in the candidate list may be stored in thehypernym-hyponym dictionary store 106 directly. Alternatively, a part orwhole of the remaining keyword pairs that may be confirmed by anoperator manually can be stored in the hypernym-hyponym dictionary store106.

As shown in FIG. 1 , the extraction system 100 may further include anuser interface 160. The user interface 160 is configured to display thecandidate list of the keyword pairs as the result of thehypernym-hyponym relation extraction, and receive an instruction fromthe operator designating an item to be stored as a hypernym-hyponym pairfrom among the candidates listed. Note that the user interface 160 candisplay a part of the candidate list involving a specific parent keyword(e.g., hypernym). The user interface 160 will be described in moredetail later.

As a result of the hypernym-hyponym relation extraction, a plurality ofhypernym-hyponym pairs may be registered in the hypernym-hyponymdictionary store 106. In FIG. 1 , a query expander 170 is shown as anexample of a use case, where the query expander 170 may perform a queryexpansion task by using the dictionary stored in the hypernym-hyponymdictionary store 106 to improve retrieval performance in patentanalysis.

In particular embodiments, each of the modules 110, 120, 130, 140 and150 in the extraction system 100 described in FIG. 1 and the submodule112, 114 of the claim structure building module 110, as well as the userinterface 160 and the query expander 170 may be implemented as softwaremodules, including program instructions and/or data structures inconjunction with hardware components, such as a processing circuitry(e.g., a CPU (Central Processing Unit), a processing core, a GPU(Graphic Processing Unit), a FPGA (Field Programmable Gate Array)), amemory, etc.; as a hardware module including electronic circuitry (e.g.,a neuromorphic chip); or as a combination thereof.

These modules 110, 112, 114, 120, 130, 140, 150, 160 and 170 describedin FIG. 1 may be implemented on a single computer system such as apersonal computer and a server machine, or a computer system distributedover a plurality of computing devices such as a computer cluster ofcomputing nodes, a client-server system, a cloud computing system, anedge computing system, etc.

With reference to FIG. 2 and FIG. 3 , a process for extractinghypernym-hyponym relation from a corpus of patent documents according toan exemplary embodiment of the present invention is described. Note thatthe process shown in FIG. 2 and FIG. 3 may be performed by processingcircuitry such as a processing unit that implements the modules of theextraction system 100 described in FIG. 1 .

As shown in FIG. 2 , the process may begin at step S100 in response tocalling the hypernym-hyponym relation extraction process. The processfrom block S101 to block S110 may be repeatedly performed for eachpatent document in the patent document corpus 102. Note that the requestof the hypernym-hyponym relation extraction may have an attribute thatdesignates the document to be analyzed. Such an attribute may includeanIPC (International Patent Classification) symbol that is a uniformpatent classification system to classify the content of the patents in ahierarchical manner. Such designation of the attribute may be done byusing regular expression, including forward match, exact match, etc. Forexample, a collection of patents having a specific IPC symbol prefix maybe designated for analysis.

FIG. 4 depicts an example of a series of patent claims as an input forthe hypernym-hyponym relation extraction. Note that the example shown inFIG. 4 is an English translation of a part of the patent claim sectionin Japanese Patent Laid-open Publication No. 2015-88333. In the patentclaim section 200, there are six claims, including a series of anindependent claim 1 and four dependent claims 3-6 that depend from claim1, which are focused on in this example for convenience. Note that aseries of the independent claim 2 and its dependent claims are outsidethe range of consideration for convenience.

Referring back to FIG. 2 , at block S102, the processing circuitry maydecompose one or more patent claims recited in each patent document ofthe patent document corpus 102 into a plurality of claim elements. Atblock S103, the processing circuitry may extract dependencies betweenthe claim elements to form one or more claim structures.

By performing the process of block S102 and block S103 for each patentdocument, a plurality of claim structures originating from the patentdocument corpus 102 are obtained. Each claim structure includes theplurality of the claim elements having respective recitations that areincluded in a corresponding patent document, and represents dependencyof the claim elements.

FIG. 5 depicts a schematic of a way of building a patent claim structureas an intermediate data structure in the process of the hypernym-hyponymrelation extraction. In FIG. 5 , there is a claim structure 210 thatincludes a six claim element 212 a-212 f. The claim structure 210 shownin FIG. 5 corresponds to the example of the series of the patent claimsshown in FIG. 4 . In FIG. 4 and FIG. 5 , the overlapping keyword thatconnects parent and child elements is encompassed by a circle with aconnecting line.

The two claim elements 212 a, 212 b (ELEMENT 1 and 2) are decomposedfrom the independent patent claim 1, as indicated by a dash box 214. Theremaining claim elements 212 c-212 f (ELEMENTS 3-6) correspond todependent claims (PATENT claims 3-6). There is a dependency between theclaim element 212 b of the independent patent claim 1 (ELEMENT 2) andthe claim element 212 c of the dependent claim 3 (ELEMENT 3). Also,there are dependencies between the claim element 212 b (ELEMENT 2), andthe claim element 212 d of the dependent claim 4 (ELEMENT 4) and theclaim element 212 e of the dependent claim 5 (ELEMENT 5), respectively.Furthermore, there is a dependency between the claim element 212 e ofthe dependent claim 5 (ELEMENT 5) and the claim element 212 f of thedependent claim 6 (ELEMENT 6). As illustrated in FIG. 5 , the claimstructure 210 has a tree like structure including a plurality of claimelements having respective recitations as nodes and parent-childrelation between a pair of parent and child elements as an edge.

Referring back to FIG. 2 , the loop from block S104 to block S109 arerepeatedly performed for each claim structure 210 originating from thepatent document corpus 102.

At block S105, the processing circuitry may extract a keyword list fromthe recitation of each claim element. For example, a keyword listincluding “unevenness”, “carbon material”, “contact” and “activematerial” may be extracted from the recitation of the claim element 212b (of FIG. 5 ) of the independent patent claim 1 (ELEMENT 2). A keywordlist including “height”, “unevenness” and “μm” may be extracted from theclaim element 212 c of the dependent claim 3 (ELEMENT 3). During thekeyword extraction, stop word removal, lemmatization and/or stemming mayalso be performed. By performing the process of block S105 for eachclaim element of the claim structure, a keyword list is obtained foreach claim element of the claim structure.

The loop from block S106 to block S108 are repeatedly performed for eachparent-child relation in each claim structure.

At block S107, the processing circuitry generates a pair of a parentkeyword list and a child keyword list for the parent-child relation byusing the keyword lists originally extracted from the elements involvedin the parent-child relation.

In order to prepare the pair of the parent keyword list and the childkeyword list, additional extraction from the original keyword list maybe performed depending on whether the element is treated as either aparent or child element in the parent-child relation. For eachparent-child relation, a parent keyword list and a child keyword listare finally extracted from the recitations of the parent and childelements, respectively.

There are mainly two methodologies of extracting the parent keywordlist. In the first methodology, the parent keyword list can be extractedso as to have only a keyword overlapping with one in the child element.In the second methodology, the parent keyword list may be extracted soas to have every keyword regardless of whether it overlaps with one inthe child element or not. In both methodologies, the child keyword listmay be extracted so as to have a keyword that does not overlap with onein the parent element. After obtaining the parent and child keywordlists, one in the parent keyword list and one in the child keyword listcan be combined to enumerate an instance of a pair of parent and childkeywords.

FIG. 6 depicts schematics of methodologies for extracting parent andchild keywords from recitations of the claim elements. In FIG. 6 , thereare four pairs of parent and child keyword lists for respectiveparent-child relations for each of two methodology (methodology-1 andmethodology-2).

For the parent child relation between the claim element 212 b (ELEMENT2) and the claim element 212 c (ELEMENT 3), there are a first keywordlist 601 a including “carbon material”, “unevenness”, “active material”and “contact” and a second keyword list 603 a including “unevenness”,“height” and “μm”.

Among the keywords in the first keyword list 601 a, only an overlappingkeyword “unevenness” is extracted as a parent keyword by the firstmethodology (methodology-1). Among the keywords in the second keywordlist 603 a, only non-overlapping keywords “height” and “μm” areextracted as child keywords.

On the other hand, in the second methodology (methodology-2), among thekeywords in the first keyword list 601 b, all of overlapping andnon-overlapping keywords “carbon material”, “unevenness”, “activematerial” and “contact” are extracted as parent keywords. Among thekeywords in the second keyword list 603 b, only non-overlapping keywords“height” and “μm” are extracted as the child keywords.

By performing the process from block S101 to block S110 (FIG. 2 ) foreach patent document in the patent document corpus 102, a huge amount ofthe pairs of the parent and child keyword lists is prepared from thepatent document corpus 102. In a particular embodiment, documentidentification (ID) may be given for each pair of the parent and childkeyword lists. After exiting the loop from block S101 to block S110(also the loop from block S104 to block S109 and the loop from blockS106 to block S108), the process proceeds to block S111, shown on FIG. 3.

At block S111, the processing circuitry calculates, for each pair of theparent and child keywords, a statistical index that indicates strengthof association between the parent and child keywords, using the hugeamount of the pairs of the parent and child keyword lists obtained fromin the patent document corpus 102. In a particular embodiment, the PMI(pointwise mutual information) can be used as the statistical index.

PMI for a pair of a parent keyword w1 and a child keyword w2 can becalculated as follows:

${{{PMI}\left( {{p = {w\; 1}},{c = {w\; 2}}} \right)} = {\log\frac{P\left( {{p = {w\; 1}},{c = {w\; 2}}} \right)}{{P\left( {p = {w\; 1}} \right)}*{P\left( {c = {w\; 2}} \right)}}}},$

where P (p=w1) represents the probability that the keyword w1 appears inthe recitation of the parent element, P (c=w2) represents theprobability that the keyword w2 appears in the recitation of the childelement, and P (p=w1, c=w2) denotes the probability that the keyword w1appears in the parent element and the keyword w2 appears in its childelement.

P (p=w1) can be calculated using a collection of parent keyword lists. P(c=w2) can be calculated in the same manner as P (p=w1). The claimelement that is involved in one relationship as the child and alsoinvolved in another relationship as the parent is counted for bothcollections as one sample. P (p=w1, c=w2) can be calculated using acollection of pairs of the parent and child keyword lists.

At block S112, the processing circuitry may filter the parent and childkeyword pairs using the statistical index to have meaningful candidatelist of the keyword pairs. If a parent and child keyword pair (p=w1,c=w2) has statistical index higher than a predetermined threshold (k),e.g., PMI (p=w1, c=w2)>k, the parent and child keyword is maintained inthe candidate list of the keyword pairs (e.g., a score S (p=w1, c=w2) isset to be PMI (p=w1, c=w2)). Otherwise, the parent and child keywordpair is discarded from the candidate list of the keyword pairs (e.g.,the score S (p=w1, c=w2) is set to be zero (0) and the keyword pair withthe score of 0 is ignored).

At block S113, the processing circuitry may remove or flag the remainingpairs by determining whether or not each keyword pair also has a reverserelationship using a predetermined threshold (t), which is a positiveparameter. IF S (p=w2, c=w1)>t, the pair is removed (e.g., the scoreS(p=w1,c=w2) is set to be 0) from the candidate list or flagged in thecandidate list.

If PMI is used as the statistical index, most of the noises may comefrom low frequent keyword pairs. Therefore, in the described embodiment,several flags that represent information relating to the reliability ofthe statistical index derived in block S111 are prepared.

At block S114, the processing circuitry may further flag the remainingpairs by determining whether or not each keyword pair has a highfrequency of co-occurrences. Those pairs having a high frequency count#(p=w1, c=w2) are flagged, where #(p=w1, c=w2) denotes a count orfrequency of the observation that the keyword w1 appears in the parentelement and the keyword w2 appears in its child element.

At block S115, the processing circuitry may further flag the remainingpairs by determining whether or not each keyword pair has appearedacross multiple different patent documents. Those pairs arising fromdifferent patent documents are flagged. It is based on the hypothesisthat those pairs that appear in more than two different patents may bemore reliable. Note that even from one patent the same pair may beextracted multiple times in extracting pairs. The documentidentification (ID) given for each pair of the parent and child keywordlists can be utilized.

At block S116, the processing circuitry may further flag the remainingpairs by determining whether or not each keyword pair has an indirectrelationship via another keyword. Those pairs (p=w1, c=w2) in whichthere exists some w3 (where w3 denotes a third keyword) satisfying PMI(p=w1, c=w3)>s and PMI (p=w3, c=w2)>s even if the frequency count#(p=w1,c=w2) is small, are flagged. It is based on the hypothesis that apair supported by combining other pairs (usually arising from differentpatents) is more reliable.

At block S117, the processing circuitry may further flag the remainingpairs by determining whether or not each keyword pair shares the samechild or parent. Those pairs (p=w1, c=w2) in which there exists some w4(where w4 denotes a fourth keyword) satisfying PMI (p=w1, c=w4)>s & PMI(p=w2, c=w4)>s are flagged. The w4 represents a shared child. Also,those pairs (p=w1, c=w2) in which there exists some w5 (where w5 denotesa fifth keyword) satisfying PMI (p=w5, c=w1)>s and PMI (p=w5, c=w2)>sare flagged. The w5 represents a shared parent. It is based on thehypothesis that if a pair shares the same child or parent, therelationship between the pair is related more closely.

At block S118, the processing circuitry outputs the candidate list ofthe keyword pairs having a hypernym-hyponym relationship based on theresult of the filtering and the evaluations in which the statisticalindex calculated for each parent child keyword pair are used. Note thata whole or a part of the candidate list involving a specific parentkeyword may be output. The process may end at block S119.

By specifying the values of the flags, only reliable pairs having highstatistical scores may be selected. In other embodiment, by using theabove-mentioned flags, some reliability scores may also be implemented.

With reference to FIG. 7 , a graphical user interface displaying theresult of the hypernym-hyponym relation extraction is described. Thegraphical user interface can be used for selecting more reliable pairsfrom candidates of hypernym/hyponym listed in the result.

In FIG. 7 , there is a window 250 that includes a table 260 with scrollbar showing the candidate list of the keyword pairs as the result of thehypernym-hyponym relation extraction; a save button 252; and a cancelbutton 254.

The table 260 includes a plurality of columns 262 a-262 f and aplurality of rows 264 a-264 d representing candidate pairs. There are aselection column 262 a, a hypernym column 262 b that shows a hypernym ina corresponding candidate pair, a hyponym column 262 c that shows ahyponym in the corresponding pair, a PMI column 262 d that shows thevalue and magnitude of the PMI calculated for the corresponding pair, amultiple document flag column 262 e, and a node share flag column 262 f.In the selection column 262 a, there is a checkbox for each row 264a-264 d to receive an instruction from the operator designating thecorresponding item to be stored as the hypernym-hyponym pair from amongthe candidate list. As shown in FIG. 7 , rows 264 c and 264 d areselected and rows 264 a and 264 b are not selected, for example.

The multiple document flag column 262 e may show a first flag (solidstar) indicating that the corresponding keyword pair has appeared acrossmultiple different patent documents or not. The node share flag column262 f may show a second flag (double circle) indicating that thecorresponding keyword pair is supported by combining the other pairs.Those pairs (p=w1, c=w2) in which there exists some w3 satisfying PMI(p=w1, c=w3)>s & PMI (p=w3, c=w2)>s are flagged by the double circles.Furthermore, the node share flag column 262 f may show a third flag(single circle) indicating that the corresponding keyword pair sharesthe same child or parent. Those pairs (p=w1 and c=w2) in which thereexist some w4 satisfying PMI (p=w4, c=w1)>s and PMI (p=w4, c=w2)>s orthere exist some w5 satisfying PMI (p=w5, c=w1)>s and PMI (p=w5, c=w2)>sare flagged by the single circles.

In response to the save button 252 being pressed down, the itemsdesignated using by the checkboxes are stored into the hypernym-hyponymdictionary store 106 as the hypernym-hyponym pair. In response to thecancel button 254 being pressed down, the obtained results arediscarded.

According to one or more embodiments of the present invention, a noveltechnology capable of extracting semantic relations from a given corpusof documents is provided while reducing manual work by a human operator.

Generally, certain expression such as “is-a” expression can be used as acue for identifying semantic relationships. However, such relationshipsare not always rigidly described in the form such as “is-a” expressionin the patent documents. According to one or more embodiments of thepresent invention, semantic relations can be preferably extracted by thenovel extraction process of the present invention, without relying onexplicit and rigid expressions such as “is-a”, since the novelextraction process can leverage certain hierarchical structure inherentin each document to extract the semantic relations.

The difficulty of the patent retrieval task may be due to the nature ofthe lexical gaps. Some of the lexical gaps arise from the mismatch ofthe “level”. For example, there is a case that an application beinganalyzed is claiming a broad idea while the prior art is describing moreconcrete and specific ideas. In this case, it is preferable that theprior art describing more concrete and specific ideas are correctlyretrieved in the prior art retrieval task. The candidate list of thekeyword pairs having a semantic relationship can be used to expand auser's query to more correctly retrieve the target document thatdescribes more concrete and specific ideas of the broad idea of thetarget query.

Note that in the aforementioned embodiments, the semantic relations tobe extracted are described to be hypernym-hyponym relations and thecorpus of the documents under analysis is described to be a corpus ofpatent documents including a patent claim section in a patentspecification. However, the present invention is not limited to theaforementioned embodiments, and semantic relationships other thanhypernym-hyponym relationships (e.g., “μm” as a more specific concept of“unevenness”) can also be extracted. Although it is preferable that thecorpus of the patent documents is employed as the document underanalysis since the novel hypernym-hyponym extraction can leverageinherent characteristics of the patent claim sections in the patentspecifications (where patent claims are natively built to describehypernym-hyponym relationships) in some embodiments, however, using acorpus of documents other than patent documents may be envisioned.

Note that the languages to which the novel semantic relation extractiontechnique is applicable is not limited and such languages may include,but by no means limited to, Arabic, Chinese, English, French, German,Japanese, Korean, Portuguese, Russian, Spanish, for instance.

EXPERIMENTAL STUDIES

A program implementing modules 110, 120, 130, 140 and 150 of theextraction system 100 in FIG. 1 and the process shown in FIG. 2 and FIG.3 according to the exemplary embodiment was coded and executed for agiven corpus of patent documents. A collection of patent claim sectionsof Japanese patent publications (publications of unexamined patentapplications or publications of granted patents if available) havingIPC=H01M and filling dates during before 1999-2017 was prepared as thecorpus of the patent documents, which corresponds to about 125,000publications. The algorithm described in the literature (S. Suzuki, etal., “Extraction of Keywords of Novelties from Patent Claims”,Proceedings of COLING 2016, the 26th International Conference onComputational Linguistics: Technical Papers, December 2016) was used tobuild the claim structures from each patent document in the givencorpus. In order to calculate the statistical index, the relevance index(r) defined in IBM™ Watson® Explorer (WEX), which is almost identical toPMI with PMI (p=w1, c=w2)=log r (p=w1, c=w2), was employed. A collectionof pairs of extracted parent and child keyword lists were used as inputdata for the WEX. The relevance index (r) was calculated by inputtingeach pair as one document into respective facets for the parent andchild.

FIG. 8 , FIG. 9 and FIG. 10 show three examples of candidate listsobtained from the given corpus using the first methodology(METHODOLOGY-1). Note that since the keyword pairs are written inJapanese, English translation is attached in the parentheses ifnecessary. As shown in FIG. 8 , FIG. 9 and FIG. 10 , it was demonstratedthat plausible results can be obtained by the novel hypernym-hyponymextraction process from the given corpus of the patent documents.

Computer Hardware Component

Referring now to FIG. 11 , a schematic of an example of a computersystem 10, which can be used for the extraction system 100, is shown.The computer system 10 is only one example of a suitable processingdevice, and is not intended to suggest any limitation as to the scope ofuse or functionality of embodiments of the invention described herein.Regardless, the computer system 10 is capable of being implementedand/or performing any of the functionality set forth hereinabove.

The computer system 10 is operational with numerous other generalpurpose or special purpose computing system environments orconfigurations. Examples of well-known computing systems, environments,and/or configurations that may be suitable for use with the computersystem 10 include, but are not limited to, personal computer systems,server computer systems, thin clients, thick clients, hand-held orlaptop devices, in-vehicle devices, multiprocessor systems,microprocessor-based systems, set top boxes, programmable consumerelectronics, network PCs, minicomputer systems, mainframe computersystems, and distributed cloud computing environments that include anyof the above systems or devices, and the like.

The computer system 10 may be described in the general context ofcomputer system-executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes.

As shown in FIG. 11 , the computer system 10 is shown in the form of ageneral-purpose computing device. The components of the computer system10 may include, but are not limited to, a processor (or processing unit)12 and a memory 16 coupled to the processor 12 by a bus including amemory bus or memory controller, and a processor or local bus using anyof a variety of bus architectures.

The computer system 10 typically includes a variety of computer systemreadable media. Such media may be any available media that is accessibleby the computer system 10, and it includes both volatile andnon-volatile media, removable and non-removable media.

The memory 16 can include computer system readable media in the form ofvolatile memory, such as random access memory (RAM). The computer system10 may further include other removable/non-removable,volatile/non-volatile computer system storage media. By way of exampleonly, the storage system 18 can be provided for reading from and writingto a non-removable, non-volatile magnetic media. As will be furtherdepicted and described below, the storage system 18 may include at leastone program product having a set (e.g., at least one) of program modulesthat are configured to carry out the functions of embodiments of theinvention.

Program/utility, having a set (at least one) of program modules, may bestored in the storage system 18 by way of example, and not limitation,as well as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules generally carry out the functions and/ormethodologies of embodiments of the invention as described herein.

The computer system 10 may also communicate with one or more peripherals24 such as a keyboard, a pointing device, a document scanning device, acar navigation system, an audio system, etc.; a display 26; one or moredevices that enable a user to interact with the computer system 10;and/or any devices (e.g., network card, modem, etc.) that enable thecomputer system 10 to communicate with one or more other computingdevices. Such communication can occur via Input/Output (I/O) interfaces22. Additionally, the computer system 10 can communicate with one ormore networks such as a local area network (LAN), a general wide areanetwork (WAN), and/or a public network (e.g., the Internet) via thenetwork adapter 20. As depicted, the network adapter 20 communicateswith the other components of the computer system 10 via a bus. It shouldbe understood that although not shown, other hardware and/or softwarecomponents could be used in conjunction with the computer system 10.Examples, include, but are not limited to: microcode, device drivers,redundant processing units, external disk drive arrays, RAID systems,tape drives, and data archival storage systems, etc.

Computer Program Implementation

The present invention may be a computer system, a method, and/or acomputer program product. The computer program product may include acomputer readable storage medium (or media) having computer readableprogram instructions thereon for causing a processor to carry outaspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may includecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein includes anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which includes one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising”, when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below, if any, areintended to include any structure, material, or act for performing thefunction in combination with other claimed elements as specificallyclaimed. The description of one or more aspects of the present inventionhas been presented for purposes of illustration and description, but isnot intended to be exhaustive or limited to the invention in the formdisclosed.

Many modifications and variations will be apparent to those of ordinaryskill in the art without departing from the scope and spirit of thedescribed embodiments. The terminology used herein was chosen to bestexplain the principles of the embodiments, the practical application ortechnical improvement over technologies found in the marketplace, or toenable others of ordinary skill in the art to understand the embodimentsdisclosed herein.

What is claimed is:
 1. A computer-implemented method for extractingsemantic relations associated with patent claim elements, the methodcomprising: generating a plurality of hierarchal structures originatingfrom a plurality of patent claims recited in a corpus of free-formpatent documents by extracting dependencies between a plurality ofdetected independent and dependent patent claim elements to generateextracted dependencies, each hierarchal structure including ancestor anddescendant claim elements having respective recitations included in acorresponding patent document as nodes and the extracted dependencies asedges representative of the detected independent and dependent claimelements, respectively; extracting, for each predetermined relationshipbetween the ancestor and descendant claim elements in the hierarchalstructures, one or more first keywords to generate a first keyword listfrom the ancestor claim element and one or more second keywords togenerate a second keyword list from the descendant claim element, thesecond keyword list being extracted such that all keywords determined tobe overlapping with the one or more first keywords are excluded from thesecond keyword list; calculating, for each pair of first and secondkeywords, a statistical index indicating strength of association betweenthe first and second keywords of the pair, using the first keyword listsand the second keyword lists, the calculating the statistical indexcomprising generating flags with specified values for pairs of interestfrom the each pair of first and second keywords for selection ofreliable pairs having comparatively high statistical scores; determiningwhether or not each keyword pair has a reverse relationship, the reverserelationship being identified by determining whether or not a determinedstatistical index for the reverse pair is higher than a predeterminedthreshold, wherein keyword pairs determined to have a reverserelationship are removed from a resultant candidate list of keywordpairs; and outputting a candidate list of keyword pairs having semantichypernym-hyponym relationships, including filtering each pair of firstand second keywords using the statistical index calculated for each pairof first and second keywords, wherein the first keyword list isgenerated from the ancestor claim element wherein a single overlappingkeyword with a single keyword in the descendant claim element and thesecond keyword list is generated from the descendant claim elementwherein a single non-overlapping keyword with the single keyword in theancestor claim element.
 2. The method of claim 1, wherein eachhierarchal structure represents dependency between claim elements in apatent claim or dependency between claim elements in a series of anindependent patent claim and one or more dependent patent claimsdepending from the independent patent claim, and each claim element inthe hierarchal structure representing one patent claim or one claimelement as a part of a patent claim.
 3. The method of claim 1, whereinobtaining the plurality of hierarchal structures further comprisesdecomposing one or more patent claims recited in each patent document ofthe corpus of documents into the plurality of claim elements.
 4. Themethod of claim 1, wherein one first keyword in the first keyword listand one second keyword in the second keyword list are combined toenumerate an instance of a pair of first and second keywords.
 5. Themethod of claim 1, wherein the first keyword list is generated from theancestor claim element so as to have one or more overlapping keywordswith one in the descendant claim element and the second keyword list isgenerated from the descendant claim element so as to have one or morenon-overlapping keywords with one in the ancestor claim element.
 6. Themethod of claim 1, wherein the first keyword list is generated from theancestor claim element so as to have one or more keywords regardless ofoverlapping with one in the descendant claim element and the secondkeyword list is generated from the descendant claim element so as tohave one or more non-overlapping keywords with one in the ancestor claimelement.
 7. The method of claim 1, wherein each statistical index is apointwise mutual information measuring an association of a first eventwhere the first keyword of the pair appears in ancestor claim elementsand a second event where the second keyword of the pair appears indescendant claim elements.
 8. The method of claim 7, wherein thepointwise mutual information for a first keyword p=w1 and a secondkeyword c=w2 is calculated as${\log\left( \frac{P\left( {{p = {w1}},{c = {w2}}} \right)}{{P\left( {p = {w1}} \right)} \star {P\left( {c = {w2}} \right)}} \right)},$where P (p=w1) represents the probability that w1 appears in a givenancestor claim element, P (c=w2) represents the probability that w2appears in a given descendent claim element, and P (p=w1, c=w2) denotesthe probability that w1 appears in the given ancestor claim element andthe keyword w2 appears in the given descendent claim element.
 9. Acomputer system for extracting semantic relations associated with patentclaim elements, by executing program instructions, the computer systemcomprising: a memory tangibly storing the program instructions; aprocessor in communications with the memory, wherein the processor isconfigured to: generate a plurality of hierarchal structures originatingfrom a plurality of patent claims recited in a corpus of free-formpatent documents by extracting dependencies between a plurality ofdetected independent and dependent patent claim elements to generateextracted dependencies, wherein each hierarchal structure includesancestor and descendant claim elements having respective recitationsincluded in a corresponding patent document as nodes and the extracteddependencies as edges representative of the detected independent anddependent claim elements, respectively; extract, for each predeterminedrelationship between the ancestor and descendant claim elements in thehierarchal structures, one or more parent keywords to generate a firstkeyword list from the ancestor claim element and one or more childkeywords to generate a second keyword list from the descendant claimelement, the second keyword list being extracted such that all keywordsdetermined to be overlapping with the one or more first keywords areexcluded from the second keyword list; calculate, for each pair of firstand second keywords, a statistical index indicating strength ofassociation between the first and second keywords of the pair, using thefirst keyword lists and the second keyword lists, the calculating thestatistical index comprising generating flags with specified values forpairs of interest from the each pair of first and second keywords forselection of reliable pairs having comparatively high statisticalscores; determine whether or not each keyword pair has a reverserelationship, the reverse relationship being identified by determiningwhether or not a determined statistical index for the reverse pair ishigher than a predetermined threshold, wherein keyword pairs determinedto have a reverse relationship are removed from a resultant candidatelist of keyword pairs; and output, to a display, a candidate list ofkeyword pairs having semantic hypernym-hyponym relationships byfiltering each pair of first and second keywords using the statisticalindex calculated for each pair of first and second keywords, wherein thefirst keyword list is generated from the ancestor claim element whereina single overlapping keyword with a single keyword in the descendantclaim element and the second keyword list is generated from thedescendant claim element wherein a single non-overlapping keyword withthe single keyword in the ancestor claim element.
 10. A computer systemfor extracting semantic relations associated with patent claim elements,by executing program instructions, the computer system comprising: amemory tangibly storing the program instructions; a processor incommunications with the memory, wherein the processor is configured to:generate a plurality of hierarchal structures originating from aplurality of patent claims recited in a corpus of free-form patentdocuments by extracting dependencies between a plurality of detectedindependent and dependent patent claim elements to generate extracteddependencies, wherein each hierarchal structure includes ancestor anddescendant claim elements having respective recitations included in acorresponding patent document as nodes and the extracted dependencies asedges representative of the detected independent and dependent claimelements, respectively; extract, for each predetermined relationshipbetween the ancestor and descendant claim elements in the hierarchalstructures, one or more parent keywords to generate a first keyword listfrom the ancestor claim element and one or more child keywords togenerate a second keyword list from the descendant claim element, thesecond keyword list being extracted such that all keywords determined tobe overlapping with the one or more first keywords are excluded from thesecond keyword list; calculate, for each pair of first and secondkeywords, a statistical index indicating strength of association betweenthe first and second keywords of the pair, using the first keyword listsand the second keyword lists, the calculating the statistical indexcomprising generating flags with specified values for pairs of interestfrom the each pair of first and second keywords for selection ofreliable pairs having comparatively high statistical scores; determinewhether or not each keyword pair has a reverse relationship, the reverserelationship being identified by determining whether or not a determinedstatistical index for the reverse pair is higher than a predeterminedthreshold, wherein keyword pairs determined to have a reverserelationship are removed from a resultant candidate list of keywordpairs; and output, to a display, a candidate list of keyword pairshaving semantic hypernym-hyponym relationships by filtering each pair offirst and second keywords using the statistical index calculated foreach pair of first and second keywords, wherein the first keyword listis generated from the ancestor claim element so as to have a singleoverlapping keyword with a single keyword in the descendant claimelement and the second keyword list is generated from the descendantclaim element so as to have a single non-overlapping keyword with thesingle keyword in the ancestor claim element.
 11. The computer system ofclaim 10, wherein each hierarchal structure represents dependencybetween claim elements in a patent claim or dependency between claimelements in a series of an independent patent claim and one or moredependent patent claims depending from the independent patent claim, andeach claim element in the hierarchal structure representing one patentclaim or one claim element as a part of a patent claim.
 12. The computersystem of claim 10, wherein the processor is further configured todecompose one or more patent claims recited in each patent document ofthe corpus of documents into the plurality of claim elements.
 13. Thecomputer system of claim 10, wherein the processor is further configuredto: determine (i) whether or not each keyword pair has a high frequencyof co-occurrences, (ii) whether or not each keyword pair has appearedacross multiple different documents, (iii) whether or not each keywordpair has an indirect relationship via another keyword and (iv) whetheror not each keyword pair shares the same ancestor or descendent claimelement.
 14. The computer system of claim 10, wherein the first keywordlist is generated from the ancestor claim element so as to have one ormore overlapping keywords with one in the descendant claim element andthe second keyword list is generated from the descendant claim elementso as to have one or more non-overlapping keywords with one in theancestor claim element.
 15. The computer system of claim 10, wherein thefirst keyword list is generated from the ancestor claim element so as tohave one or more keywords regardless of overlapping with one in thedescendant claim element and the second keyword list is generated fromthe descendant claim element so as to have one or more non-overlappingkeywords with one in the ancestor claim element.
 16. The computer systemof claim 10, wherein each statistical index is a pointwise mutualinformation measuring an association of a first event where the firstkeyword of the pair appears in ancestor claim elements and a secondevent where the second keyword of the pair appears in descendant claimelements.
 17. A computer program product for extracting semanticrelations associated with patent claim elements, the computer programproduct comprising a computer readable storage medium having programinstructions embodied therewith, the program instructions executable bya computer to cause the computer to perform a method comprising:generating a plurality of hierarchal structures originating from aplurality of patent claims recited in a corpus of free-form patentdocuments by extracting dependencies between a plurality of detectedindependent and dependent patent claim elements to generate extracteddependencies, each hierarchal structure including ancestor anddescendant claim elements having respective recitations included in acorresponding patent document as nodes and the extracted dependencies asedges representative of the detected independent and dependent claimelements, respectively; extracting, for each predetermined relationshipbetween the ancestor and descendant claim elements in the hierarchalstructures, one or more first keywords to generate a first keyword listfrom the ancestor claim element and one or more second keywords togenerate a second keyword list from the descendant claim element, thesecond keyword list being extracted such that all keywords determined tobe overlapping with the one or more first keywords are excluded from thesecond keyword list; calculating, for each pair of first and secondkeywords, a statistical index indicating strength of association betweenthe first and second keywords of the pair, using the first keyword listsand the second keyword lists, the calculating the statistical indexcomprising generating flags with specified values for pairs of interestfrom the each pair of first and second keywords for selection ofreliable pairs having comparatively high statistical scores; determiningwhether or not each keyword pair has a reverse relationship, the reverserelationship being identified by determining whether or not a determinedstatistical index for the reverse pair is higher than a predeterminedthreshold, wherein keyword pairs determined to have a reverserelationship are removed from a resultant candidate list of keywordpairs; and outputting a candidate list of keyword pairs having semantichypernym-hyponym relationships, including filtering each pair of firstand second keywords using the statistical index calculated for each pairof first and second keywords, wherein the first keyword list isgenerated from the ancestor claim element wherein a single overlappingkeyword with a single keyword in the descendant claim element and thesecond keyword list is generated from the descendant claim elementwherein a single non-overlapping keyword with the single keyword in theancestor claim element.
 18. The computer program product of claim 17,wherein each hierarchal structure represents dependency between claimelements in a patent claim or dependency between claim elements in aseries of an independent patent claim and one or more dependent patentclaims depending from the independent patent claim, and each claimelement in the hierarchal structure representing one patent claim or oneclaim element as a part of a patent claim.
 19. The computer programproduct of claim 17, wherein the method further comprises: determining(i) whether or not each keyword pair has a high frequency ofco-occurrences, (ii) whether or not each keyword pair has appearedacross multiple different documents, (iii) whether or not each keywordpair has an indirect relationship via another keyword and (iv) whetheror not each keyword pair shares the same ancestor or descendent claimelement.